Improved NMR-data-compliant protein structure modeling captures context-dependent variations and expands the scope of functional inference

Das, NR and Chaudhury, KN and Pal, D (2022) Improved NMR-data-compliant protein structure modeling captures context-dependent variations and expands the scope of functional inference. In: Proteins: Structure, Function and Bioinformatics .

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Abstract

Nuclear magnetic resonance (NMR) spectroscopy can reveal conformational states of a protein in physiological conditions. However, sparsely available NMR data for a protein with large degrees of freedom can introduce structural artifacts in the built models. Currently used state-of-the-art methods deriving protein structure and conformation from NMR deploy molecular dynamics (MD) coupled with simulated annealing for building models. We provide an alternate graph-based modeling approach, where we first build substructures from NMR-derived distance-geometry constraints combined in one shot to form the core structure. The remaining molecule with inadequate data is modeled using a hybrid approach respecting the observed distance-geometry constraints. One-shot structure building is rarely undertaken for large and sparse data systems, but our data-driven bottom-up approach makes this uniquely feasible by suitable partitioning of the problem. A detailed comparison of select models with state-of-art methods reveals differences in the secondary structure regions wherein the correctness of our models is confirmed by NMR data. Benchmarking of 106 protein-folds covering 38–282 length structures shows minimal experimental-constraint violations while conforming to other structure quality parameters such as the proper folding, steric clash, and torsion angle violation based on Ramachandran plot criteria. Comparative MD studies using select protein models from a state-of-art method and ours under identical experimental parameters reveal distinct conformational dynamics that could be attributed to protein structure–function. Our work is thus useful in building enhanced NMR-evidence-based models that encapsulate the contextual secondary and tertiary structure variations present during the experimentation and expand the scope of functional inference.

Item Type:	Journal Article
Publication:	Proteins: Structure, Function and Bioinformatics
Publisher:	John Wiley and Sons Inc
Additional Information:	The copyright for this article belongs to John Wiley and Sons Inc.
Keywords:	bottom-up approach; conformation; distance-geometry; nonlinear optimization; structure solution
Department/Centre:	Division of Electrical Sciences > Electrical Engineering Division of Interdisciplinary Sciences > Computational and Data Sciences Division of Physical & Mathematical Sciences > Mathematics
Date Deposited:	04 Jan 2023 06:02
Last Modified:	04 Jan 2023 06:02
URI:	https://eprints.iisc.ac.in/id/eprint/78711

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